ReviewBiomedicines2026
Autophagy in Cancer: Context-Dependent Regulation and Precision Nanomedicine-Enabled Therapeutic Targeting.
Review in Biomedicines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Autophagy Modulation in Cancer Therapy: Navigating the Dual Roles to Overcome Chemoresistance.Health science reports · 2026Article
- Review
- Autophagy in Ovarian Cancer, an Opportunity or an Additional Threat?International journal of molecular sciences · 2026Review
- The interplay between autophagy and immunogenic cell death: nanomaterial-based strategies for cancer immunotherapy.Journal of nanobiotechnology · 2026Review
- Autophagy Modulation in Cancer Immunotherapy, Emerging Molecular Targets and Drug Selection Strategies.International journal of molecular sciences · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Autophagy is a highly conserved cellular degradation process essential for maintaining cellular homeostasis, yet its role in cancer is fundamentally context dependent. Increasing evidence indicates that autophagy suppresses tumor initiation by preserving genomic and metabolic integrity, while paradoxically supporting tumor progression, therapy resistance, and immune evasion at advanced stages. This functional duality presents a major challenge for therapeutic targeting and largely reflects the spatiotemporal heterogeneity of autophagy regulation across tumor stages, cancer cell subpopulations, and the tumor microenvironment (TME). In this review, we argue that autophagy-related proteins should be conceptualized as context-dependent therapeutic nodes rather than universally actionable targets. We systematically examine key autophagy regulators, including Beclin-1, p62/SQSTM1, mTOR, and p53, and analyze how their functions are shaped by tumor stage, genetic background, and microenvironmental cues such as hypoxia, immune pressure, and stromal interactions. We further highlight the pivotal role of the TME in determining autophagy dependency and therapeutic vulnerability, providing mechanistic insight into why autophagy modulation without microenvironmental consideration often yields inconsistent outcomes. From a precision medicine perspective, we discuss how nanotechnology-based delivery systems enable spatially and temporally controlled modulation of autophagy, thereby addressing intratumoral heterogeneity and reducing systemic toxicity. By integrating molecular profiling, TME characteristics, and nanomedicine-enabled targeting strategies, this review outlines a rational framework for exploiting autophagy in cancer therapy. Together, these insights provide a foundation for the development of context-aware, autophagy-targeted interventions and advance the pursuit of more effective and personalized cancer treatments.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.